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At least 181 records · Page 10

Comparison of UNL laser imaging and sizing system and a phase Doppler system for analyzing sprays from a NASA nozzle

Research was conducted on characteristics of aerosol sprays using a P/DPA and a laser imaging/video processing system on a NASA MOD-1 air assist nozzle being evaluated for use in aircraft icing research. Benchmark tests were performed on monodispersed particles and on the NASA MOD-1 nozzle under identical lab operating conditions. The laser imaging/video processing system and the P/DPA showed agreement on a calibration tests in monodispersed aerosol sprays of + or - 2.6 micron with a standard deviation of + or - 2.6 micron. Benchmark tests were performed on the NASA MOD-1 nozzle on the centerline and radially at 0.5 inch increments to the outer edge of the spray plume at a distance 2 ft downstream from the exit nozzle. Comparative results at two operation conditions of the nozzle are presented for the two instruments. For the 1st case studied, the deviation in arithmetic mean diameters determined by the two instruments was in a range of 0.1 to 2.8 micron, and the deviation in Sauter mean diameters varied from 0 to 2.2 micron. Severe operating conditions in the 2nd case resulted in the arithmetic mean diameter deviating from 1.4 to 7.1 micron and the deviation in the Sauter mean diameters ranging from 0.4 to 6.7 micron.

Alexander, Dennis R.↗

Software For Computing Selected Functions

Technical memorandum presents collection of software packages in Ada implementing mathematical functions used in science and engineering. Provides programmer with function support in Pascal and FORTRAN, plus support for extended-precision arithmetic and complex arithmetic. Valuable for testing new computers, writing computer code, or developing new computer integrated circuits.

Grant, David C.↗

Depth-size tradeoffs for neural computation

The tradeoffs between the depth (i.e., the time for parallel computation) and the size (i.e., the number of threshold gates) in neural networks are studied. The authors focus the study on the neural computations of symmetric Boolean functions and some arithmetic functions. It is shown that a significant reduction in the size is possible for symmetric functions and some arithmetic functions, at the expense of a small constant increase in depth. In the process, several neural networks which have the minimum size among all the known constructions have been developed. Results on implementing symmetric functions can be used to improve results about arbitrary Boolean functions. In particular, It is shown that any Boolean function can be computed in a depth-3 neural network with O(2n/2) threshold gates; it is also proven that a minimum number of threshold gates are required.

Siu, Kai-Yeung↗

Defining the IEEE-854 floating-point standard in PVS

A significant portion of the ANSI/IEEE-854 Standard for Radix-Independent Floating-Point Arithmetic is defined in PVS (Prototype Verification System). Since IEEE-854 is a generalization of the ANSI/IEEE-754 Standard for Binary Floating-Point Arithmetic, the definition of IEEE-854 in PVS also formally defines much of IEEE-754. This collection of PVS theories provides a basis for machine checked verification of floating-point systems. This formal definition illustrates that formal specification techniques are sufficiently advanced that is is reasonable to consider their use in the development of future standards.

Miner, Paul S.↗

Modified-Signed-Digit Optical Computing Using Fan-Out

Experimental optical computing system containing optical fan-out elements implements modified signed-digit (MSD) arithmetic and logic. In comparison with previous optical implementations of MSD arithmetic, this one characterized by larger throughput, greater flexibility, and simpler optics.

Liu, Hua-Kuang↗

A PVS Prover Strategy Package for Common Manipulations

Sequent manipulations for an interactive prover such as PVS can often be labor intensive. We describe an approach to tactic-based proving for improved interactive deduction in specialized domains. An experimental package of strategies (tactics) and support functions has been developed for PVS to reduce the tedium of arithmetic manipulation. Included are strategies aimed at algebraic simplification of real-valued expressions as well as term-access techniques applicable in arbitrary settings. The approach is general enough to serve in other mathematical domains and for provers other than PVS. This report presents the full set of arithmetic strategies and discusses how they are invoked within the prover. Included is a description of the extended expression notation for accessing terms as well as a substitution technique provided for higher-order strategies. Several sample proofs are displayed in full to show how the strategies might be used in practice.

DiVito, Ben L.↗

Benchmarking Memory Performance with the Data Cube Operator

Data movement across a computer memory hierarchy and across computational grids is known to be a limiting factor for applications processing large data sets. We use the Data Cube Operator on an Arithmetic Data Set, called ADC, to benchmark capabilities of computers and of computational grids to handle large distributed data sets. We present a prototype implementation of a parallel algorithm for computation of the operatol: The algorithm follows a known approach for computing views from the smallest parent. The ADC stresses all levels of grid memory and storage by producing some of 2d views of an Arithmetic Data Set of d-tuples described by a small number of integers. We control data intensity of the ADC by selecting the tuple parameters, the sizes of the views, and the number of realized views. Benchmarking results of memory performance of a number of computer architectures and of a small computational grid are presented.

Frumkin, Michael A.↗

Multinode reconfigurable pipeline computer

A multinode parallel-processing computer is made up of a plurality of innerconnected, large capacity nodes each including a reconfigurable pipeline of functional units such as Integer Arithmetic Logic Processors, Floating Point Arithmetic Processors, Special Purpose Processors, etc. The reconfigurable pipeline of each node is connected to a multiplane memory by a Memory-ALU switch NETwork (MASNET). The reconfigurable pipeline includes three (3) basic substructures formed from functional units which have been found to be sufficient to perform the bulk of all calculations. The MASNET controls the flow of signals from the memory planes to the reconfigurable pipeline and vice versa. the nodes are connectable together by an internode data router (hyperspace router) so as to form a hypercube configuration. The capability of the nodes to conditionally configure the pipeline at each tick of the clock, without requiring a pipeline flush, permits many powerful algorithms to be implemented directly.

Nosenchuck, Daniel M.↗

Economical Implementation of a Filter Engine in an FPGA

A logic design has been conceived for a field-programmable gate array (FPGA) that would implement a complex system of multiple digital state-space filters. The main innovative aspect of this design lies in providing for reuse of parts of the FPGA hardware to perform different parts of the filter computations at different times, in such a manner as to enable the timely performance of all required computations in the face of limitations on available FPGA hardware resources. The implementation of the digital state-space filter involves matrix vector multiplications, which, in the absence of the present innovation, would ordinarily necessitate some multiplexing of vector elements and/or routing of data flows along multiple paths. The design concept calls for implementing vector registers as shift registers to simplify operand access to multipliers and accumulators, obviating both multiplexing and routing of data along multiple paths. Each vector register would be reused for different parts of a calculation. Outputs would always be drawn from the same register, and inputs would always be loaded into the same register. A simple state machine would control each filter. The output of a given filter would be passed to the next filter, accompanied by a "valid" signal, which would start the state machine of the next filter. Multiple filter modules would share a multiplication/accumulation arithmetic unit. The filter computations would be timed by use of a clock having a frequency high enough, relative to the input and output data rate, to provide enough cycles for matrix and vector arithmetic operations. This design concept could prove beneficial in numerous applications in which digital filters are used and/or vectors are multiplied by coefficient matrices. Examples of such applications include general signal processing, filtering of signals in control systems, processing of geophysical measurements, and medical imaging. For these and other applications, it could be advantageous to combine compact FPGA digital filter implementations with other application-specific logic implementations on single integrated-circuit chips. An FPGA could readily be tailored to implement a variety of filters because the filter coefficients would be loaded into memory at startup.

Kowalski, James E.↗

Model Checking with Edge-Valued Decision Diagrams

We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library. We provide efficient algorithms for manipulating EVMDDs and review the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi- Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools. Compared to the CUDD package, our tool is several orders of magnitude faster

Roux, Pierre↗

Enhanced Graphics for Extended Scale Range

Enhanced Graphics for Extended Scale Range is a computer program for rendering fly-through views of scene models that include visible objects differing in size by large orders of magnitude. An example would be a scene showing a person in a park at night with the moon, stars, and galaxies in the background sky. Prior graphical computer programs exhibit arithmetic and other anomalies when rendering scenes containing objects that differ enormously in scale and distance from the viewer. The present program dynamically repartitions distance scales of objects in a scene during rendering to eliminate almost all such anomalies in a way compatible with implementation in other software and in hardware accelerators. By assigning depth ranges correspond ing to rendering precision requirements, either automatically or under program control, this program spaces out object scales to match the precision requirements of the rendering arithmetic. This action includes an intelligent partition of the depth buffer ranges to avoid known anomalies from this source. The program is written in C++, using OpenGL, GLUT, and GLUI standard libraries, and nVidia GEForce Vertex Shader extensions. The program has been shown to work on several computers running UNIX and Windows operating systems.

Hanson, Andrew J.↗

Kodiak: An Implementation Framework for Branch and Bound Algorithms

Recursive branch and bound algorithms are often used to refine and isolate solutions to several classes of global optimization problems. A rigorous computation framework for the solution of systems of equations and inequalities involving nonlinear real arithmetic over hyper-rectangular variable and parameter domains is presented. It is derived from a generic branch and bound algorithm that has been formally verified, and utilizes self-validating enclosure methods, namely interval arithmetic and, for polynomials and rational functions, Bernstein expansion. Since bounds computed by these enclosure methods are sound, this approach may be used reliably in software verification tools. Advantage is taken of the partial derivatives of the constraint functions involved in the system, firstly to reduce the branching factor by the use of bisection heuristics and secondly to permit the computation of bifurcation sets for systems of ordinary differential equations. The associated software development, Kodiak, is presented, along with examples of three different branch and bound problem types it implements.

Smith, Andrew P.↗

Defining Baconian Probability for Use in Assurance Argumentation

The use of assurance cases (e.g., safety cases) in certification raises questions about confidence in assurance argument claims. Some researchers propose to assess confidence in assurance cases using Baconian induction. That is, a writer or analyst (1) identifies defeaters that might rebut or undermine each proposition in the assurance argument and (2) determines whether each defeater can be dismissed or ignored and why. Some researchers also propose denoting confidence using the counts of defeaters identified and eliminated-which they call Baconian probability-and performing arithmetic on these measures. But Baconian probabilities were first defined as ordinal rankings which cannot be manipulated arithmetically. In this paper, we recount noteworthy definitions of Baconian induction, review proposals to assess confidence in assurance claims using Baconian probability, analyze how these comport with or diverge from the original definition, and make recommendations for future practice.

Graydon, Patrick J.↗

Characterizing the System Impulse Response Function from Photon-Counting LiDAR Data

NASA's Multiple Altimeter Beam Experimental LiDAR (MABEL) is an aircraft-based photon-counting laser altimeter designed as a simulator to test measurement techniques and algorithms for Advanced Topographic Laser Altimeter System (ATLAS), the sole instrument on NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. By measuring the time of flight, pointing angle, and absolute position for individual photons, ICESat-2 provides detailed elevation measurements of earth's surface. Calculating accurate and precise elevations requires an understanding of how photons interact with surfaces, and characterization of the photon distribution after returning from surfaces. Neither MABEL nor ATLAS records the transmitted laser pulse shape, relying instead on aggregating several pulses worth of photons, often using histograms, to characterize the pulse shape. In this paper, we assess the limitations of using histograms and propose a more robust method to describe MABEL's system impulse-response function using an exponentially modified Gaussian distribution. We also provide standard error estimates for the arithmetic mean and standard deviation calculations, and for exponentially modified Gaussian parameters using a Monte Carlo sensitivity analysis. We apply this method to photon returns from a sea ice lead and from a dry salt lake bed as case studies for estimating the standard error associated with sample size for the arithmetic mean and standard deviation, and for the exponentially modified Gaussian parameters. We use these standard errors to calculate the minimum number of photons required to find both Gaussian and exponentially modified Gaussian distribution parameters within 3 cm of their parent population values.

photoncounting↗

Register file soft error recovery

Register file soft error recovery including a system that includes a first register file and a second register file that mirrors the first register file. The system also includes an arithmetic pipeline for receiving data read from the first register file, and error detection circuitry to detect whether the data read from the first register file includes corrupted data. The system further includes error recovery circuitry to insert an error recovery instruction into the arithmetic pipeline in response to detecting the corrupted data. The inserted error recovery instruction replaces the corrupted data in the first register file with a copy of the data from the second register file.

97 MATHEMATICS AND COMPUTING↗

Evaluation of Low Power ARM Processors for Monte Carlo Particle Transport: MCNP6 on the ARM Cortex-A8 - Paper 83

In the push towards exascale computing, the limiting factors are power requirements and heat dissipation. Using current technology, the power required to drive an exascale supercomputer would near 400-MW. Clearly, future computing hardware will have to be more energy efficient in order to achieve exascale performance. Most of the current research in advanced computing architectures is in the use of standard CPUs with accelerators. However, these accelerators are not generally supported by the traditional scientific programming languages (C, C++, and Fortran) and the scientific software must be tailored specifically to take advantage of the accelerators. Large scale scientific software (hundreds-of-thousand to millions of lines of code) can not be easily ported to the computing platform du jour. The widespread use of low power ARM based processors in the mobile computing market offer a low power alternative to accelerators that are also supported by the traditional scientific programming languages and programming paradigms such as MPI and OpenMP. Computing architectures for scientific computing are often assessed using standard benchmarks such as LINPACK benchmark or using suites of mini-applications that are greatly simplified stand-ins for scientific software. Often the real applications that will deployed on the scientific supercomputers are not ported or tested until delivery of the machines. In order to evaluate the use of ARM processors for scientific computing the Monte Carlo particle transport code, MCNP version 6 was compiled on the ARM Cortex-A8 and a set of benchmark problems were used to assess performance in comparison to an Intel Xeon E5-2670 and the low power Intel Atom N270. MCNP is a continuous energy Monte Carlo particle transport code in development at Los Alamos National Laboratory since 1977. MCNP is used to transport neutrons, photon, electrons, and charged particles using continuous energy interaction data. It is commonly used in fields of nuclear power, nuclear medicine, radiation protection, and high-energy physics through-out the world. MCNP version 6 is approximately 450 thousand lines of code, written primary in Fortran90, with some C and C++. MCNP supports distributed multiprocessing using MPI and threading with OpenMP. The ARM Cortex-A8 executes MCNP6 using about twice as much power as the Intel Xeon E5-2670 and about the same amount of power as the Intel Atom N270. However, these results are encouraging for the use of low-power ARM chips in future supercomputers. The ARM Cortex-A8 is a 32-bit CPU and it's NEON general-purpose SIMD (single-instruction multiple data) engine does not support double-precision floating-point arithmetic. More recent ARM processors (ARM Cortex-A53 and Cortex-A57) support 64-bit addressing and have NEON co-processors that support double-precision floating-point arithmetic. ARM claims that the A50 series delivers a performance increase of 15 times the Cortex-A8 performance for similar power usage. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Managing the Performance/Error Tradeoff of Floating-point Intensive Applications

Modern embedded systems are becoming more reliant on real-valued arithmetic as they employ mathematically complex vision algorithms and sensor signal processing. Double-precision floating point is the most commonly used precision in computer vision algorithm implementations. A single-precision floating point can provide a performance boost due to less memory transfers, less cache occupancy, and relatively faster mathematical operations on some architectures. However, adopting it can result in loss of accuracy. Identifying which parts of the program can run in single-precision floating point with low impact on error is a manual and tedious process. In this paper, we propose an automatic approach to identify parts of the program that have a low impact on error using shadow-value analysis. Our approach provides the user with a performance/error tradeoff, using which the user can decide how much accuracy can be sacrificed in return for performance improvement. We illustrate the impact of the approach using a well known implementation of Apriltag detection used in robotics vision. In conclusion, we demonstrate that an average 1.3x speedup can be achieved with no impact on tag detection, and a 1.7x speedup with only 4% false negatives.

97 MATHEMATICS AND COMPUTING↗

Modeling protected species distributions and habitats to inform siting and management of pioneering ocean industries: A case study for Gulf of Mexico aquaculture

Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.

54 ENVIRONMENTAL SCIENCES↗